[CVPR 2019]Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
论文地址：https://arxiv.org/abs/1901.02970 github链接：https://github.com/hughw19/NOCS_CVPR2019 类别级6D物体位姿和尺寸估计的标准化物体坐标空间 简介 本文的目标是估计RGB-D图像中从未见过的物体实例的6D位姿和尺寸。与“实例级”6D位姿估计任务相反，作者假设在训练或测试期间没有精确的CAD模型可用。为
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相关文章
- 1. Segmentation-driven 6D Object Pose Estimation论文理解
- 2. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes—2017（笔记）
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- 4. 【paper】DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion 6D姿态估计
- 5. Single-Stage 6D Object Pose Estimation——6D姿态估计
- 6. (26) Distribution-Aware Coordinate Representation for Human Pose Estimation
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- 8. 2020.09.23读MaskedFusion: Mask-based6D object pose estimation
- 9. PointSetNet：Point-Set Anchors for Object Detection,Instance Segmentation and Pose Estimation
- 10. 论文笔记01——PoseCNN：A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes